Diagnostic-i

A one stop point for your medical diagonosis made both for the patient and the doctor's help.Check for various problems like Mental health and bone issue.Alongwith that you can check your lab reports.

Built at ETHforAll

Created on 19th February 2023

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This project has been flagged for recycling pre-existing work

Diagnostic-i

A one stop point for your medical diagonosis made both for the patient and the doctor's help.Check for various problems like Mental health and bone issue.Alongwith that you can check your lab reports.

The problem Diagnostic-i solves

Digonosis-i is a full fledged product that will be used for multiple medical related things,broadly classified into 3 categories-
1.)Disease detection using xray-a patients xray images will be uploaded by him/her and the deep larning model designed will predict whether they have the specific disease or not.
2.).It will be used to check whether the person need to get him/her admitted to the hospital for medical treament on the basis of the laboratory result that the user will upload on the website and the machine learning based AI classifier will detect the need for admitting. This feature further contains 3 sub features:-
1.)Pneumonia detection
2.)Brain Tumor detection using MRI scan
3.) Osteoarthritis detection using Knee Xray
3.)Checker for the Mental Health treatment requirnment -The last but not the least feature is checking the status of the mental health of a person for which a model is designed to take various input features and predict whether or not the person should take mental health treatment.

Challenges I ran into

The problem we ran into was:-
1.) training such huge models in this small time period for the hackathon.
2.)Transferring the image data from the user i.e. frontend to the model

Tracks Applied (25)

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Chainlink

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Quicknode: Built on QuickNode RPC

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QuickNode: Token API

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Mantle

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Mantle

ConsenSys: Metamask Snaps

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ConsenSys: Truffle + Infura

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Connext: General Track

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Polywrap

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Technologies used

TensorFlow

React.js

Discussion

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